BIT

Research

The Brain Image Team (BIT) Lab focuses on imaging unique properties of the brain. When most people consider using magnetic resonance imaging (MRI) to study the brain, the envision the high-resolution structural images that show the shape of the brain. Although this is very useful, in our research group we also use more advanced forms of MRI to image unique properties of the brain. These methods include cerebrovascular imaging to image the microvascular (capillary bed) and macroscopic (larger arteries of the brain); diffusion and functional MRI (to study the underlying wiring and activation of the brain). We use these methods with advanced data analytics to yield answers in areas of the cerebrovascular disease (i.e., stroke, aneurysm) and aging physiology (i.e., brain aging, neurodegeneration, and dementia).

We have a holistic approach to research vertically ranging across technology development, image acquisition and reconstruction, data analytics and machine learning, and now. At UCalgary we have infrastructure including a MR Engineering Technology Lab (coming soon), high field MRI systems (3x 3T Human MRI systems, 9.4T Animal MRI system). High Performance Computing infrastructure through UCalgary and the Digital Research Alliance of Canada (>200 TB of data storage, and several >100,000 core compute clusters). We have access to perhaps one of the largest collections of neuroimage data in the world including the UK Biobank, National Institutes of Mental Health, Human Connectome Project, Alzheimer's Disease Neuroimaging Initiative, Open Access Series of Imaging Studies, among many others. On our compute clusters we have assembled many neuroimaging tools including custom tools to facilitate research analyses. This overall approach vertically integrates brain imaging research for comprehensive experience and internally leverages expertise.

Image acquisition and reconstruction for MRI visualization

Data collection and reconstruction of new MRI images is core to our research program. In this theme, we build and program hardware to collect novel measurements of the brain. We do pulse sequence programming to manipulate the timing of MRI gradients and radiofrequency pulses to estimate unique properties of the brain. These unique acquisition schemes work in concert with advanced reconstruction algorithms to yield quantitative parameters.

Data Analytics and Machine Learning

Our group has gathered perhaps the largest amount of neuroimaging data available, and this is leveraged against the high-performance computing infrastructure available at the institution and federally to enable advanced data analytics and machine learning experiments. We are using typical neuroimaging pipelines in concert with custom algorithms developed in house. Here the aim to formulate the highest values applications and questions to answer, and then robustly demonstrate with the data we have on hand.

Modeling of brain circuits to inspire the next generation of intelligent algorithms

Boarding on computational neuroscience applications we aim to undertake emulation of brain function based on neuroimaging data. Given our access to copious amounts of brain imaging data, in particular, diffusion weighted imaging (DTI), functional MRI (fMRI), electroencephalogram (EEG) and magnetoencephalography; we use tools such as the Virtual Brain to simulate the brain under stroke and dementia.